Combining formal and informal contract enforcement in a developed legal system: a latent class approach

2018 ◽  
Vol 15 (3) ◽  
pp. 521-537
Author(s):  
Károly Mike ◽  
Gábor Kiss
Keyword(s):  
Latent Class ◽  
Third Party ◽  
Data Driven ◽  
Contract Enforcement ◽  
Governance Structures ◽  
System A ◽  
Community Norms ◽  
Level Data ◽  
Contractual Governance ◽  
Enforcement Mechanisms

AbstractHow do firms combine a broad range of contract enforcement mechanisms into coherent governance structures? How often are distinct structures used in an economy? We develop a new empirical approach, based on latent class analysis, to answer these questions. Economy-level data from Hungary are used to derive a data-driven typology of contractual governance between firms. The joint use of law, morality, self-enforcing contracts, reputation and community norms is examined. They are shown to be combined into bilateral, third-party or comprehensive governance structures. The crucial governance choice is whether to move beyond bilateralism and, if yes, whether to use a mixture of (formal and informal) third-party mechanisms as a substitute or a complement. Complementarity is much more common. We find no instances of ‘impersonal exchange’; the law never stands alone. By implication, economic development may be best understood as a process from a narrower towards a broader set of enforcement mechanisms.

Impact of Platform Owner’s Entry on Third-Party Stores

2020 ◽  
Vol 31 (4) ◽  
pp. 1467-1484 ◽  
Author(s):  
Shu He ◽  
Jing Peng ◽  
Jianbin Li ◽  
Liping Xu
Keyword(s):  
Mobile App ◽  
The Other ◽  
Third Party ◽  
Data Driven ◽  
Defensive Strategy ◽  
Important Decision ◽  
Online Marketplaces ◽  
Level Data ◽  
Demand Reduction ◽  
The Impact

One important decision faced by the owners of online marketplaces is whether they should enter the market and sell products directly to customers. In this study, we provide data-driven insights to managers by empirically investigating the impact of a platform owner’s entry on the demand of third-party stores and their potential reactions using transaction level data from a large e-commerce platform. Contrary to previous studies in mobile app platforms, our study shows that the demand of competing third-party stores decreases with the entry of the platform, especially for large third-party stores. We further show that the demand reduction is significant only in the offline channel and the reduction results from third-party stores’ defensive strategy to divert their offline customers away from the platform (i.e., disintermediation). Our findings indicate that platforms should carefully evaluate the nature of their markets before entering the market to compete with complementors, because they may lead third-party sellers to disintermediate from the platform. On the other hand, from the perspective of third-party sellers, disintermediation might be an overreaction to the entry of the platform, because their online demand is not significantly affected by platform entry based on our analyses.

New Evidence on the Construct Validity of the ASI-3 and the Dimensional Conceptualization of Trait Anxiety Sensitivity From IRT Modeling

2017 ◽  
Vol 33 (3) ◽  
pp. 181-189 ◽  
Author(s):  
Christoph J. Kemper ◽  
Michael Hock
Keyword(s):  
Construct Validity ◽  
Anxiety Sensitivity ◽  
Latent Class ◽  
Dimensional Structure ◽  
Sensitivity Index ◽  
Response Scale ◽  
Established Risk Factor ◽  
Irt Models ◽  
Level Data ◽  
Extreme Response

Abstract. Anxiety Sensitivity (AS) denotes the tendency to fear anxiety-related sensations. Trait AS is an established risk factor for anxiety pathology. The Anxiety Sensitivity Index-3 (ASI-3) is a widely used measure of AS and its three most robust dimensions with well-established construct validity. At present, the dimensional conceptualization of AS, and thus, the construct validity of the ASI-3 is challenged. A latent class structure with two distinct and qualitatively different forms, an adaptive form (normative AS) and a maladaptive form (AS taxon, predisposing for anxiety pathology) was postulated. Item Response Theory (IRT) models were applied to item-level data of the ASI-3 in an attempt to replicate previous findings in a large nonclinical sample (N = 2,603) and to examine possible interpretations for the latent discontinuity observed. Two latent classes with a pattern of distinct responses to ASI-3 items were found. However, classes were indicative of participant’s differential use of the response scale (midpoint and extreme response style) rather than differing in AS content (adaptive and maladaptive AS forms). A dimensional structure of AS and the construct validity of the ASI-3 was supported.

RiRiShun Logistics: Home Appliance Delivery Data for the 2021 Manufacturing & Service Operations Management Data-Driven Research Challenge

2021 ◽  
Author(s):  
Xiaolong Guo ◽  
Yugang Yu ◽  
Gad Allon ◽  
Meiyan Wang ◽  
Zhentai Zhang
Keyword(s):  
Operations Management ◽  
Service Operations ◽  
Optimization Techniques ◽  
Data Driven ◽  
Analytical Models ◽  
Data Set ◽  
Service Operations Management ◽  
Level Data ◽  
Home Appliance ◽  
Research Challenge

To support the 2021 Manufacturing & Service Operations Management (MSOM) Data-Driven Research Challenge, RiRiShun Logistics (a Haier group subsidiary focusing on logistics service for home appliances) provides MSOM members with logistics operational-level data for data-driven research. This paper provides a detailed description of the data associated with over 14 million orders from 149 clients (the consigners) associated with 4.2 million end consumers (the recipients and end users of the appliances) in China, involving 18,000 stock keeping units operated at 103 warehouses. Researchers are welcomed to develop econometric models, data-driven optimization techniques, analytical models, and algorithm designs by using this data set to address questions suggested by company managers.

Reputations, Relationships, and Contract Enforcement

2007 ◽  
Vol 45 (3) ◽  
pp. 595-628 ◽  
Author(s):  
W. Bentley MacLeod
Keyword(s):  
Contract Enforcement ◽  
Market Mechanisms ◽  
Efficient Level ◽  
Enforcement Mechanisms ◽  
Real Costs

When the quality of a good is at the discretion of the seller, how can buyers assure that the seller provides the mutually efficient level of quality? Contracts that provide a bonus to the seller if the quality is acceptable or impose a penalty on the seller if quality is unacceptable can, in theory, provide efficient incentives. But how are such contracts enforced? While the courts can be used, doing so involves high real costs. Informal enforcement, involving a loss of reputation and future access to the market for any party that defaults on a contract, may often be a better alternative. This paper explores the use of both formal and informal enforcement mechanisms, provides a rationale for a variety of observed market mechanisms, and then generates a number of testable hypotheses.

scholarly journals Mahindra First Choice

2021 ◽  
pp. 354-362
Author(s):  
Ben Jackson ◽  
Genevieve Joy
Keyword(s):  
Third Party ◽  
Repair System ◽  
Market Failures ◽  
System A ◽  
Car Market ◽  
System P ◽  
First Choice ◽  
Used Car ◽  
The Creation ◽  
Trust Information

Mahindra Firstchoice illustrates the process of ecosystem orchestration in the context of the second-hand car market in India. It describes how Mahindra Firstchoice mapped the ecosystem in relation to six key parties—consumers who were buyers, consumers who were sellers, car manufacturers, independent used-car dealers, independent car service workshops, and banks. It then identified the bottlenecks and ‘pain points’ that afflicted the six parties. The used-car market did not function properly because of lack of trust, information, and transparency and Mahindra Firstchoice worked with the parties to identify solutions to the market failures. These involved, amongst other things, the creation of third-party car inspection services, the establishment of a multi-brand car-dealer franchise, a warranty system, a bluebook of second-hand prices and transactions, and a car diagnosis and repair system.

Data Analysis Services Related to the IoT and Big Data

Web Services ◽  
2019 ◽  
pp. 882-903
Author(s):  
Izabella V. Lokshina ◽  
Barbara J. Durkin ◽  
Cees J.M. Lanting
Keyword(s):  
Big Data ◽  
Data Analysis ◽  
Business Models ◽  
Third Party ◽  
Data Driven ◽  
Easy Access ◽  
Provision Of Services ◽  
And Control ◽  
Measurement And Control ◽  
The Internet Of Things

The Internet of Things (IoT) provides the tools for the development of a major, global data-driven ecosystem. When accessible to people and businesses, this information can make every area of life, including business, more data-driven. In this ecosystem, with its emphasis on Big Data, there has been a focus on building business models for the provision of services, the so-called Internet of Services (IoS). These models assume the existence and development of the necessary IoT measurement and control instruments, communications infrastructure, and easy access to the data collected and information generated by any party. Different business models may support opportunities that generate revenue and value for various types of customers. This paper contributes to the literature by considering business models and opportunities for third-party data analysis services and discusses access to information generated by third parties in relation to Big Data techniques and potential business opportunities.

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